KernelChars: Kernel characteristics

In locpol: Kernel Local Polynomial Regression

Kernel characteristics

Description

For a given kernel these functions return some of the most commonly used numeric values related to them.

Usage

	RK(K)
	RdK(K)
	mu2K(K)
	mu0K(K)
	K4(K)
	dom(K)

Arguments

K	A kernel as given in Kernels

Details

Most of these functions are implemented as an attribute of every kernel. For the computations of the numeric value for these quantities, see references.

Value

A numeric value returning:

RK	The L_2 norm of K.
RdK	The L_2 norm of the derivative of K.
mu2K	The second order moment of K.
mu2K	The zeroth order moment of K.
dom	The support of K.
K4	The fourth order autoconvolution of K at x=0.

Author(s)

Jorge Luis Ojeda Cabrera.

References

Fan, J. and Gijbels, I. Local polynomial modelling and its applications\/. Chapman & Hall, London (1996).

Wand, M.~P. and Jones, M.~C. Kernel smoothing\/. Chapman and Hall Ltd., London (1995).

See Also

Kernels, Compute kernel values.

Examples

	##	Note that lower and upper params are set in the definition to
	##	use 'dom()' function.
	g <- function(kernels)
	{
		mu0 <- sapply(kernels,function(x) computeMu0(x,))
		mu0.ok <- sapply(kernels,mu0K)
		mu2 <- sapply(kernels,function(x) computeMu(2,x))
		mu2.ok <- sapply(kernels,mu2K)
		Rk.ok <- sapply(kernels,RK)
		RK <- sapply(kernels,function(x) computeRK(x))
		K4 <- sapply(kernels,function(x) computeK4(x))
		res <- data.frame(mu0,mu0.ok,mu2,mu2.ok,RK,Rk.ok,K4)
		res
	}
	g(kernels=c(EpaK,gaussK,TriweigK,TrianK))

locpol documentation built on Nov. 29, 2022, 9:05 a.m.